Automatic segmentation of kidney and kidney tumor based on 3D convolutional neural networks

Authors
Qiao, Pengchong
Zhao, Bin
Liu, Zhiyang

Issue Date
2019

Publisher
University of Minnesota Libraries Publishing

Type
Article

Abstract
Kidney cancer is a huge threat to humans, and the surgery is the most common treatment. For clinicians, knowing the morphology of the kidney and kidney tumor in advance may be helpful for surgery. Automatic segmentation of kidney and kidney tumor is a promising approach for these efforts. In this paper, we proposed a based 3D convolutional neural network to segment kidney and kidney tumor using the data from the 2019 Kidney Tumor Segmentation Challenge.

Identifiers
doi: 10.24926/548719.086